analyze-demand

A method for analysing what customers are trying to accomplish in a particular industry, using Jobs to Be Done, a framework that groups customers by the task they hire a product to perform.

In plain words
What is it for?
Use it to define customer segments by their jobs, assess cross-category substitutes and switching likelihood, identify willingness-to-pay drivers, and track demand signals.
Why use it?
It reveals alternative solutions customers might switch to, what drives their willingness to pay, and early signs that demand is changing.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/agent-engineer-master/skill-engineer/analyze-demand
Any agent
npx skills add Agent-Engineer-Master/skill-engineer --skill analyze-demand
Clone the repo
git clone --depth 1 https://github.com/Agent-Engineer-Master/skill-engineer

Made for: Claude Code, Codex.

Per session 208 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,949 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00208 $0.02949
Opus 5 $0.00104 $0.01474
Sonnet 5 $0.00042 $0.00590
Haiku 4.5 $0.00021 $0.00295

Measured 2d ago against content hash 3b65b675589a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

analyze-demand scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_demand.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

<!-- Built with Agent Engineer Master — get your own production-ready skill: www.agentengineermaster.com/skill-engineer -->
strategy/industry-analysis/analyze-demand/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analyze Demand

For a defined industry, produce a structural demand-side analysis. Output: demand.md that names the JOB the industry's customers are hiring solutions to perform, segments by that job (not demographics), and surfaces substitution risk before it shows in share data.

The discipline: Demand-side analysis is the early-warning system for disruption. Five Forces tells you the structure; profit pools tell you where the money sits today; competitive arena tells you who is winning. Demand analysis tells you whether the question being asked is about to change. JTBD originated in product design; at industry-analysis level it aggregates outcomes across the buyer population to spot cross-category substitution before market-share data moves.

Iron rules:

  • Every fact-claim carries a V/C/A/I tag — see ../_shared/provenance-tagging.md.
  • ≥1 JTBD identified with ALL THREE components (functional / emotional / social) named — even if a component is "minimal" or "absent," state it explicitly. Do not omit.
  • ≥2 customer segments defined by the job they hire the product to do, not by demographic or firmographic attributes. "Young urban professionals" or "mid-market SaaS companies" fail this test; "buyers hiring the product to reduce time-to-decision in regulatory submissions" passes.
  • ≥1 substitution risk with named substitute candidate (cross-category preferred), explicit switching cost, and stated likelihood. Naming "general competition" or "other vendors" fails.
  • Substitution analysis section MUST use the standard heading ## Substitution Risk (exact wording, level-2 heading). Downstream consumers parse by heading; variants fail.
  • WTP drivers stated per segment — NOT a single price. Drivers explain WHY this segment will or won't pay.
  • ≥1 named demand signal with a measurable leading indicator (search trend, channel check, expert-interview language shift, regulatory filing shift, etc.). Lagging metrics like revenue fail.

Process

1. Intake — lock the analysis frame

Confirm: industry slug, geographic scope, B2B / B2C / hybrid, focal value-chain layer (must match the layer used in map-five-forces if running in orchestrator mode), buying-unit definition (individual / household / SMB / enterprise procurement committee). Read references/jtbd-methodology.md and references/customer-segmentation.md. Note any substitution threats already flagged in working/five-forces.md (orchestrator mode) — they are the priority candidates to chase in step 4.

Read the full file on GitHub · 134 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 134 lines · 208 tokens per session scan C 3b65b675589a

Subscribe to this mod's changes

analyze-demand is a skill published in the GitHub repository Agent-Engineer-Master/skill-engineer (8 stars, last pushed 1mo ago), licensed MIT. It adds 208 tokens to every session and 2,949 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.